Free
$0Free plan available.
Otter.ai is an AI meeting assistant that records meetings, takes notes in real-time, and generates automated summaries. It supports real-time transcription, live chat, automated summaries, insights, and action items. Otter.ai offers solutions for business, sales, education, and media, helping users to capture and share insights from their meetings.
Otter.ai automatically joins Zoom, Google Meet, and Microsoft Teams meetings to record and transcribe. Users can follow the transcription live via the web, iOS, or Android apps. Otter AI Chat allows users to ask questions and generate content such as emails or status updates, while action items are automatically identified and assigned.
Yes. Sign in to your account, navigate to Settings, select “Upgrade to Business,” and follow the provided instructions.
We accept credit and debit card payments via the Otter.ai website, as well as in-app purchases processed through your Apple App Store or Google Play account.
Yes, we provide a 20% discount on Otter Pro Monthly and Annual plans for students and teachers who register with an email address ending in .edu.
Free plan available.
Use these comparison pages to understand the trade-offs between the models most relevant to Otter.ai.
Compare Gemini 1.0 Pro Deprecated and Gemini 2.0 Flash across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
Compare Gemini 1.0 Pro Deprecated and Gemini 2.5 Flash across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
Compare Gemini 2.0 Flash Lite and Gemini 2.0 Flash across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
Compare Gemini 2.5 Flash and Gemini 2.0 Flash across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus long-context workloads.
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